Objective: To study the association between temperature and daily mortality from June 1, 2006 to December 31, 2009 in Guangzhou.
Methods: Time series approach was used to estimate the impact of temperature on the rates of total and cause-specific daily mortality. We fitted generalized additive Poisson regression using non-parametric smooth functions to control for the long-term time trend, day of week, air pollution and other weather variables.
Results: A slight sloping U-like relationship between the total mortality and temperature was found, with an optimum average temperature (temperature with lowest mortality risk) value of 19.7°C in Guangzhou. For temperature above the optimum value, the relative risk of total mortality increased by 3.0% (RR=1.030, 95%CI: 1.011-1.050) for each increase of degree in Celsius. For average temperature below the optimum value, the relative risk of total mortality and diseases of circulatory system had a 3.3% (RR=0.967, 95%CI: 0.936-0.997) decrease and a 3.6% (RR=0.964, 95%CI: 0.935-0.994) increase, for each degree of Celsius increase, respectively.
Conclusion: Our findings showed that the temperature had an impact on the daily mortality in Guangzhou. Countermeasures needed to be taken to reduce the temperature related mortality.